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A Gaussian approach for continuous time models of the short-term interest rate

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  • JUN YU

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  • PETER C. B. PHILLIPS

    ()

Abstract

This paper proposes a Gaussian estimator for nonlinear continuous time models of the short-term interest rate. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite-sample performance of the proposed procedure offers an improvement over the discrete approximation method proposed by Nowman (1997). An em-pirical application to US and British interest rates is given.

Suggested Citation

  • Jun Yu & Peter C. B. Phillips, 2001. "A Gaussian approach for continuous time models of the short-term interest rate," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-3.
    • Handle: RePEc:ect:emjrnl:v:4:y:2001:i:2:p:3
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    Cited by:

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    2. Zi-Yi Guo, 2017. "Order Flow and Exchange Rate Dynamics in Continuous Time: New Evidence from Martingale Regression," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 507-512.
    3. Xiao Huang, 2011. "Quasi‐maximum likelihood estimation of discretely observed diffusions," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 241-256, July.
    4. Baviera, Roberto & Santagostino Baldi, Tommaso, 2019. "Stop-loss and leverage in optimal statistical arbitrage with an application to energy market," Energy Economics, Elsevier, vol. 79(C), pages 130-143.
    5. Chang, Yoosoon, 2012. "Taking a new contour: A novel approach to panel unit root tests," Journal of Econometrics, Elsevier, vol. 169(1), pages 15-28.
    6. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.
    7. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    8. Roberto Baviera & Tommaso Santagostino Baldi, 2017. "Stop-loss and Leverage in optimal Statistical Arbitrage with an application to Energy market," Papers 1706.07021, arXiv.org.
    9. Jian Huang & Masahito Kobayashi & Michael McAleer, 2010. "Testing the Box-Cox Parameter for an Integrated Process," Working Papers in Economics 10/77, University of Canterbury, Department of Economics and Finance.
    10. K. Fergusson & E. Platen, 2015. "Application Of Maximum Likelihood Estimation To Stochastic Short Rate Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    11. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    12. Ali Ataullah & Andrew Higson & Mark Tippett, 2006. "Real (adaptation) options and the valuation of equity: some empirical evidence," Abacus, Accounting Foundation, University of Sydney, vol. 42(2), pages 236-265, June.
    13. Wymer Clifford R., 2012. "Continuous-Tme Econometrics of Structural Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(2), pages 1-28, April.
    14. Guo, Zi-Yi, 2017. "Martingale Regressions for a Continuous Time Model of Exchange Rates," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 40-45.
    15. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    16. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Economics Working Paper Archive at Hunter College 406, Hunter College Department of Economics, revised 2005.

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